What the data for this category looks like
Core data for this category comes from scheduling systems, fault work orders, monitoring alerts, and organizational contact directories. Four document types are maintained daily: duty schedules, handover records, escalation contact lists, and daily duty reports. Duty schedules include structured fields such as date, duty shift, and responsible party contact information. Handover records document unresolved technical issues and follow-up progress. Escalation contact lists mark the permission scope of second-tier support personnel. Daily duty reports summarize the day’s response status. Data updates occur daily or weekly, adjusted dynamically as duty rotations shift and work advances.
What constraints do these characteristics impose on the reranking and hybrid retrieval workflow
This category’s data includes both structured fields and unstructured content. Hybrid retrieval must support both precise field matching and semantic association. Relying solely on a single retrieval mode risks missing critical information. Data updates occur daily or weekly. Retrieval must prioritize recalling recently updated entries to prevent returning outdated scheduling or handover records. Most fields relate to personnel, shifts, and technical issues. The reranking step must prioritize matching duty personnel on active shifts and unresolved issues. This ensures retrieval results align with the real-time needs of frontline technical support. Data sources are scattered, so hybrid retrieval must support data in different formats. This avoids recall failures due to format mismatches.
Configuration Settings
This guide is compatible with FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
usingReRank | Enabled | This category requires prioritizing precise matches for active duty shifts and unresolved technical issues. Reranking filters low-relevance historical scheduling and handover records |
similarity | 0.75–0.85 | This category’s data includes structured shift and contact fields. Filtering out entries with overly low semantic matching avoids interfering with core retrieval results |
limit | Top 8–12 entries | This category’s data updates daily. Retrieving too many entries at once increases retrieval latency, while this range covers that day’s duty shifts, recent handover items, and escalation contact information |
searchMode | hybrid | This category contains both structured fields and unstructured content. Hybrid retrieval balances precise matching of shifts and contacts with semantic association for unresolved issues |
| Question Optimization | Enabled | Converts user pre-sales or support queries into retrieval terms better suited to duty data, improving the relevance of recall results |
Three Common Configuration Mistakes
- Symptom: Retrieval latency exceeds 30 seconds after enabling question optimization and reranking. Cause: No limit is set on the number of single-recall entries or the reranking model’s processing scope, leading to loading unnecessary historical data such as scheduling and handover records.
- Symptom: Request errors appear in the interface after configuring a local reranking model. Cause: The deployment port and file path of the local model are not correctly configured in FastGPT v4.17.0, or the model version is incompatible with the current platform.
- Symptom: No reranking results appear in online recall tests after enabling reranking and knowledge base indexing. Cause: The reranking toggle is not enabled during the retrieval step, or the
similaritythreshold is set too high, filtering all valid recalled entries.
How to Verify Successful Configuration
- Navigate to the knowledge base retrieval test page in FastGPT, enter a query that includes the current duty shift, and confirm that the returned results prioritize displaying the contact information of that day’s duty personnel.
- Check the retrieval logs to confirm that reranking model call records exist and that the number of returned results matches the configured
limitvalue. - Adjust the
similaritythreshold, observe changes in the relevance of recall results, and confirm that the configuration takes effect. - Test the connectivity of the local reranking model and confirm that there are no request error logs.
The values provided here are common starting points and should be evaluated against the user’s own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.